Last month, 1,092 people visited my Apify Store page. 281 of them clicked through to an actor's input page. 419 hit the Start button and actually ran something. Those numbers are small by SaaS standards. But for a solo developer in Nairobi who did not know JavaScript 4 months ago, they represent something real.
Here is what I learned watching that funnel take shape.
The Funnel Nobody Tells You About
Apify gives you analytics on every actor. The flow looks like this:
1,092 page views. 281 input page views. 419 actor starts.
That last number being higher than input page views confused me at first. It happens because returning users skip the description page and go straight to the input form. Repeat usage matters more than first impressions. Some users run a single actor 200+ times. One person ran my WHOIS lookup 262 times in a month.
The lesson? Retention is baked into the product, not the marketing. If the tool works well on the first run, they come back without being asked.
Where Traffic Actually Comes From
I expected Twitter and dev.to articles to drive most of my growth. I was wrong.
69% of my traffic comes from Apify Store search. People type "google scholar scraper" or "email validator" into the Apify marketplace and find my tools. This is basically app store SEO. The actors with the best README files, clear titles, and specific keywords rank higher.
12% comes from Google. Those same README files index on Google, so people searching for niche data problems land on my actors directly. Two of my actors rank on the first page for their target keywords.
8% comes from the Apify Console, meaning existing users discover new actors while browsing their dashboard.
The remaining 11% is social media, articles, and direct links. All that tweeting and article writing moves the needle, but not as much as writing a good README.
The China and Singapore Surprise
39% of my traffic comes from China and Singapore. I built every actor assuming my users would be in the US and Europe. Completely wrong.
It makes sense in hindsight. Developers and data teams in Asia need the same tools. English language documentation works globally. And the Apify Store does not have geographic barriers.
This changed how I think about naming and descriptions. I stopped using US specific references and started writing for a global audience. Small shift, big impact on discoverability.
From Scrapers to Solutions
My early actors had names like "LinkedIn Employee Scraper" and "YouTube Transcript Extractor." They worked fine but competed with dozens of free alternatives.
The actors that grew fastest were the ones I repositioned as solutions. "Google Maps Lead Intel" instead of "Google Maps Scraper." "Entity OSINT Analyzer" instead of "Entity Search." "Competitor Intelligence" instead of "LinkedIn Comparison Tool."
Same code underneath. Different framing. The solution named actors attract buyers. The scraper named actors attract tire kickers who want everything free.
The Power User Pattern
Most users try an actor once. Maybe twice. Then they leave. But a small group of users runs the same actor hundreds of times. These are the users who pay for everything.
My WHOIS lookup has one user with 262 runs. Google Scholar has someone at 230. AI Content Detector at 132. These power users are building automated pipelines that call my actors on a schedule or in bulk.
The business model only works because of them. Optimizing for power users (faster response times, better error handling, higher rate limits) matters more than converting first time visitors.
What I Would Do Differently
I wasted time on Reddit (got banned from r/webscraping for posting too aggressively), cold DMs (zero conversions), and Discord communities (untrackable results).
If I started over today, I would spend 80% of my time writing great README files with clear keywords and 20% writing technical articles on dev.to and Hashnode. Everything else is noise.
53 actors. 869 users. 1,092 page views. Built solo from Nairobi.
The tools that grow are the ones that solve a specific problem well and show up when someone searches for that problem. That is the entire playbook.
I build data APIs and scrapers on the Apify Store. If you need structured data from any website, check out my portfolio: george.the.developer on Apify
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